Accessibility Study of mHealth Systems Based on The Internet of Things (IoT)

Abstract

The Internet of Things (IoT) has become part of people's daily life, allowing physical and digital contact. The rise of mobile devices and scientific and technological advances in health have led to breakthroughs in meeting consumer needs. mHealth refers to using mobile devices to improve healthcare services, increase medical care, and reduce costs. Mobile cloud computing (MCC) lets users bypass mobile device limits on processing, storage, and battery life. A body area network uses implanted wireless sensors to remotely monitor patients (WBAN). These networks collect and distribute data for disease diagnosis and prevention. This mix of technologies allows hospitals and clinics new ways to treat and monitor patients. This research examines IoT availability in mHealth. The analysed architecture includes wireless sensors to monitor patients, an intra-BAN, a mobile device with a battery and communication interfaces, an extra-BAN with Wi-Fi and 4G connectivity, and a cloud environment to store data. Hierarchical models were developed using RBD and continuous-time Markov chains (CTMC). Each component's MTTF (mean time to failure) and MTTR (mean time to repair) values are used to quantify system or section availability. Experiments were conducted to test mHealth availability parameters. Intra-BAN, Zigbee, or Bluetooth protocols have no meaningful impact on system availability. For households, two small routers in the extra-BAN are more effective than one large router. Finally, backup batteries and power banks boost availability. The offered models can help developers and maintainers scale mHealth systems based on service needs.